Patient Position Control for Scanning

ABSTRACT

For patient positioning for scanning, a current pose of a patient is compared to a desired pose. The desired pose may be based on a protocol or a pose of the same patient in a previous examination. Any differences in pose, such as arm position, leg position, head orientation, and/or torso orientation (e.g., laying on side, back, or stomach), are communicated. By changing the current pose of the patient to be more similar to the desired pose, a more consistent and/or registerable dataset may be acquired by scanning the patient.

TECHNICAL FIELD

The present teachings relate generally to patient position for scanning,such as positioning a patient in a desired pose for an initial scanand/or in a same pose for each of a sequence of scans.

BACKGROUND

In cases where a patient is to be scanned at multiple timepoints, it isbeneficial to register results with a previous dataset to detect changesbetween scans. Due to differences in the patient or patient pose, thedataset results of the scans being compared may not be spatiallyaligned. Deformable registration transforms one dataset to match theother dataset voxel by voxel. These three-dimensional deformableregistration methods are more likely to succeed if the changes from onescan to the next are minimal. For example, the arms being up in oneacquisition and down in another may make registration less reliable.

For more reliable registration, it is advantageous to position thepatient in a similar way for a current scan as the patient waspositioned for a previous scan. Manual positioning may be inconsistent.Precise alignment across treatments is desired for radiation therapy. Inthese cases, the patient is fixed during each application in a plasticmold that is fabricated before the first acquisition, or markers aretattooed on the patient skin for aligning with a projected target duringeach treatment. These approaches are expensive or invasive. In a generalscanning situation, especially for a first diagnostic scan, it is notknown that a follow-up scan is needed, so expensive or invasiveapproaches may not be used.

SUMMARY

By way of introduction, the preferred embodiments described belowinclude methods, systems, and computer readable media with instructionsfor patient positioning for scanning. A current pose of a patient iscompared to a desired pose. The desired pose may be based on a protocolor a pose of the same patient in a previous examination. Any differencesin pose, such as arm position, leg position, head orientation, and/ortorso orientation (e.g., laying on side, back, or stomach), arecommunicated. By changing the current pose of the patient to be moresimilar to the desired pose, a more consistent and/or registerabledataset may be acquired by scanning the patient.

In a first aspect, a method is provided for patient positioning forscanning. A first pose of a patient is determined from a firstexamination. The first pose is determined from a depth camera image,scan data from the first examination, or both. A depth camera, themedical scanner, or both senses a patient on a bed of a medical scannerfor a second examination at a different time than the first examination.A second pose of the patient is determined from the sensing. The firstpose is compared to the second pose. A change in pose based on thecomparing is transmitted so that the second pose matches the first pose.

In a second aspect, a method is provided for patient positioning forscanning. A depth camera, the medical scanner, or both captures datarepresenting a patient on a bed of a medical scanner. A first pose ofthe patient is determined from the data. The first pose is compared to asecond pose. A change in pose of the patient on the bed so that thefirst pose matches the second pose is transmitted. The medical scannerscans the patient after conforming to the change in the pose.

In a third aspect, a system is provided for patient positioning forscanning. A diagnostic imager has a patient bed. A camera is configuredto detect a surface of a body on the patient bed. A processor isconfigured to determine a pose of the body from the surface and identifya difference in the pose of the body from another pose. A display isconfigured to indicate a change to reduce the difference.

The present invention is defined by the following claims, and nothing inthis section should be taken as a limitation on those claims. Furtheraspects and advantages of the invention are discussed below inconjunction with the preferred embodiments and may be later claimedindependently or in combination.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flow chart diagram of one embodiment of a method for patientpositioning for scanning;

FIG. 2 is a flow chart diagram of another embodiment of the method forpatient positioning for scanning;

FIG. 3 illustrates one embodiment of a system for patient positioningfor scanning;

FIG. 4 is a block diagram of one embodiment of a system for patientpositioning for scanning; and

FIG. 5 is a block diagram of another embodiment of a system for patientpositioning for scanning.

DETAILED DESCRIPTION

Patient position is adjusted for scanning. Data from a previousexamination of that patient may be used to align the patient roughly inthe same position. The adjustment is automatically identified andcommunicated to a user or patient. Where the patient is scanned acrossmultiple time points, more consistent acquisition across time points isperformed. Comparisons of scans from different times points may benefitfrom the consistency.

FIG. 1 shows one embodiment of a method for patient positioning forscanning. The method includes determining a current pose of a patient ona bed of a medical scanner and comparing the current pose to a desiredpose. Any differences in pose are communicated to the patient ortechnician so that the patient's pose is altered to the desired pose. Inthe embodiment of FIG. 1, the desired pose is from any source, such as aprotocol, previous scan, or previous depth camera image (e.g., pointcloud).

FIG. 2 is a flow chart diagram of another embodiment of the method forpatient positioning for scanning. FIG. 2 shows the source of the desiredpose determination of act 30 as scan data and/or depth camera image froma previous examination of the patient. FIG. 2 concludes withrecommending the change in pose whereas FIG. 1 includes performing thesubsequent or current scan once the patient is in the desired pose. Theresults of the scan may be registered with results from previous scans.

FIGS. 1 and 2 show data flows to properly orient the patient beforeacquisition. In one embodiment, a previous acquisition of the patientincludes a computed tomography (CT) volume and/or a color image+depth(e.g., red green blue-depth (RGB-D) image). The depth may be with ablack and white or other image. An image without depth information maybe used, such as by detecting a pose from the image. In examples below,RGB-D is used. These previous data are used to determine the pose heldduring the original acquisition. In the current acquisition, data fromthe RGB-D camera and/or from a imaging scan are used to determine thecurrent patient pose. The differences between previous and currentpatient poses are computed, and recommended pose changes are determined.As a simple example, if the patient had theft left arm down in theprevious acquisition but theft left arm is up prior to the currentacquisition, this difference is determined and then communicated to theoperator or patient. Once the pose is determined to be the same asbefore, the current acquisition can proceed.

The methods of FIGS. 1 and 2 may include additional, different, or feweracts. For example, acts 40 and 42 of FIG. 1 are not performed or areincluded in the acts of FIG. 2. As another example, the desired pose ofact 30 is based on previous acquisition in FIG. 1 as shown in FIG. 2, orthe desired pose is determined in act 30 of FIG. 2 without the previousacquisition. In yet another example, acts are repeated to verify thecurrent pose as correct prior to the scanning of act 40.

In the examples discussed herein, computed tomography is used.Performing a scout scan in computed tomography to obtain a topogram mayresult in additional radiation being applied to the patient. The scandata from the scout scan may be used to determine pose. Rather thanusing scout, navigation, or other alignment scans, depth camerainformation may be used to properly position the patient. The use of thedepth data from a depth camera may avoid the additional radiation ortime to pre-scan. In other embodiments, the medical scan data is forpositron emission tomography (PET), single photon emission tomography(SPECT), magnetic resonance, ultrasound, fluoroscopy, x-ray, or othermedical diagnostic scanning.

The acts are performed in the order shown (top to bottom or numerical)or a different order. For example, act 30 is performed at a same time,prior to, or after act 32 or 34.

A medical scanner, processor, server, workstation, computer, otherdevice, or combinations of devices perform the acts of FIGS. 1 and 2. Inone embodiment, the system of FIG. 3, of FIG. 4, or of FIG. 5 performsthe methods. In another embodiment, a medical imager performs act 40. Acontroller or processor of the medical imager performs acts 30, 34, 36,and 42. A camera or the medical imager performs act 32. The controller,processor, network interface, a projector, speaker, or display performsact 38.

In act 30, a desired pose is determined. The desired pose is determinedby look-up from a database or memory. Alternatively or additionally, thedesired pose is determined by a processor (e.g., by a computer,controller of the medical scanner, and/or server). Data may be processedto determine the desired pose.

The desired pose is a position of the patient desired for a currentscan. The desired pose may include whether the arms are by the head orby the torso, the arms are at the side against or spaced away from thetorso, the legs together or spaced apart, the head or the feet at anentry end of the patient bed (i.e., head orientation), and/or thepatient or torso laying on a side, back, or front on the patient bed(i.e., torso orientation). Other posing or body part positioning may beincluded in the pose, such as the rotation of the head relative to thetorso or shoulders, bending of elbows and/or knees, hand position,finger position, and/or use of spacers between the patient and thepatient bed.

In one embodiment, the desired pose represents a generic ideal patientposition. A given diagnosis or treatment workflow follows a protocol.The protocol includes the desired pose. For example, the arms are to bepositioned by the head for a CT scan of the lower abdomen for digestive,liver, or kidney scanning. The desired pose is defined by the scanningapplication. A model of a generic patient in the desired pose and/orparameterized descriptors (e.g., “legs together”) are provided as thedesired pose.

In another embodiment, the desired pose is determined from a previousexamination. The examination corresponds to a different day. To assesstreatment or further diagnosis, a same type of scan may be performed atdifferent times, such as once a month, once a year, once every fewyears, or any other frequency. Each scan is performed at a differentexamination (e.g., a different appointment). To assist comparison ofresults from the scans of the different examinations, the patient poseis the same for each scan. The pose used in one or more previous scansis used as the desired pose.

In one embodiment, the initial scan is known to be an initial scan. Thepose for the initial scan is based on a protocol, physician, ortechnician. The same pose is desired for each of the subsequent scans.The protocol or data from the initial scan may be used to determine thedesired pose. In other embodiments, the initial scan is prior todiagnosis and/or realization that subsequent scan or scans are to beperformed. Thus, a protocol may not define the pose. Instead, datacaptured from the initial or prior examination is used to determine thepose and that pose is then used for later scans as the desired pose. Forexample, a patient is scanned to determine whether there are signs oflung cancer. Where there are signs, a course of radiation therapy may beprescribed. After the treatment or interspersed with the treatment,additional scans are performed. The course is not known until after theinitial scan. The scan data or other data captured for the initial scanmay be used to determine the desired pose to be used for the subsequentscans. This first pose is established without a plan for treatment. Thepose of the initial scan may be a pose dictated by protocol or not.

A processor determines the desired pose from scan data, a depth cameraimage, or both scan data and a depth camera image. The previous scanprovides scan data representing the patient on the patient bed. The datamay represent a volume, such as representing the patient in threedimensions (e.g., voxels). The data may represent a plane, such asscanning a cross-section or projecting to a detector plane (e.g., x-rayor fluoroscopy) representing the patient in two-dimensions (e.g.,pixels). The data is in a scan format or a display format. The scan datais an image derived from scanning, is data used to create an image, oris data obtained by scanning but not used for imaging. The scan datarepresents the patient on the patient bed.

Where a camera, such as a depth camera, acquires an image of the patientin the previous scan, the image (e.g., RGB+D) may be used to determinethe pose. A still image or video plus depth information is used tocompute the patient position. The camera image is used as or to create apoint cloud, surface mesh, or other three-dimensional representation ofthe patient. Alternatively, a camera without depth information is used.The resulting image provides pose information in two dimensions.

For the depth camera, a depth sensor measures depths relative to asurface of a patient. Any depth sensor may be used. The depth sensorprovides three-dimensional sensor image data or depth data. In someembodiments, the depth data is captured via a camera. Any now known orlater developed depth camera may be used, such as stereo cameras,structured-light devices (e.g., Microsoft Kinect, ASUS Xtion),time-of-flight devices (e.g., Creative TOF cameras), and combinationsthereof. In some embodiments, the three-dimensional sensor image datafurther includes color image data (e.g., an RGB image). Any opticaldepth camera may be used to measure the surface of the patient, with orwithout clothes.

The placement of one or more cameras in the medical image scanning room(e.g., a CT scanning room, a PET scanning room, a MR scanning room,and/or the like) may be determined empirically to achieve optimalperformance of the analytics. Various factors that may influenceperformance include, for example, the ease and/or expense of sensorinstallation, patient visibility constraints (e.g., the quality of theobtainable data), and sensor noise characteristics. For example, withstructured-light devices and time-of-flight devices, noise tends toincrease as distance from the sensor increases. Moreover, depending onwavelength, noise may also increase near the sensor. Thus, sensor noisecharacteristics may be balanced against the field of view of the sensorwhen determining placement of a sensor.

To achieve reliable surface reconstruction from depth images, thecameras may be mounted such that the cameras have an unobstructed viewof the patient lying on the patient table. Depending on the sensor noisecharacteristics (e.g., image quality and/or resolution of captureddepth-image), the camera(s) may be mounted close to the scanner tablewhile still being able to keep the entire or majority of the patientwithin the camera view. FIGS. 3 and 5 show example placements of thedepth sensor 18 relative to the patient 14 and the medical scanner 16.In FIG. 3, the camera depth sensor 18 is positioned on the ceiling abovethe patient table and in front of an entry into the bore of the medicalscanner 16. In FIG. 5, the camera depth sensor 18 is positioned on thegantry of the medical scanner 16.

Only one or more than one camera may be used, such as a first camerapositioned on the ceiling directly above a patient table, and a secondcamera positioned at one end of the patient table. The twolocations—overhead and angled—each have their advantages anddisadvantages. For example, with an overhead camera, the analyticsproblem is more constrained and results that are more accurate may beobtained. However, the overhead camera presents challenges from aninstallation perspective since the camera is to be mounted on theceiling. By contrast, the angled camera may have a lower installationoverhead (e.g., the camera may even be attached to the gantry at thetime of shipment). However, with the angled view, some patient data maybe obscured.

In one embodiment, the depth measurements from the sensor provide a 3Dpoint cloud of the patient. The 3D point cloud may be reconstructed andused for further processing. Data may also be captured from both camerasand fused to obtain a more accurate 3D point cloud. Since the twocameras are fixed, the cameras may be stereo calibrated (e.g., camerapositions may be estimated relative to one another). Given thecalibration information, the data from the two cameras may then becombined to obtain a denser point cloud representation of the scene.

The scan data or depth image may be rendered, segmented, and/or imageprocessed to determine the pose. The previous scan or depth data may berendered so that the patient outline (skin, body) is visible. Therendering is used as the pose.

In one embodiment, template matching is used to determine the pose.Different templates representing different poses are registered with thescan data or the depth data (e.g., point cloud). The template with thegreatest similarity provides the pose. Instead of template matching,classification may be used. For example, a probabilistic boosting treeor other machine learning is used to learn to distinguish between posesand/or to output pose parameters based on an input vector. The inputvector (e.g., HAAR wavelets) is derived from the scan and/or depth data.The machine learning uses many examples of input vectors with known poseinformation (i.e., training data) to learn to distinguish between poses.Hierarchal, sequential binary, or other combinations of classifiers maybe used for different aspects of pose, such as one classifier for torsoorientation and another for arm position. Alternatively, one classifierprovides values for all the pose parameters. Once trained, theclassifier or classifiers use calculated input vectors from the scan ordepth data to classify the pose of the patient in the correspondingexamination.

In another embodiment, template matching, machine learning, or otherimage process identifies landmarks. For example, the hand, elbow, arm,head, hip, shoulders, knees, feet, legs, and/or other body parts (e.g.,nose or eyes) are identified. The relative position of the landmarksindicates the pose.

In yet another embodiment, a parameterized deformable model is fit to apoint cloud of the depth camera image, to the scan data, or to both. Themodel may be a skeleton or connected lines. The fitting positions theskeletonized lines to the data. In another approach, the model is athree-dimensional mesh (e.g., polygon mesh), but other surfaces orrepresentations (e.g., point cloud) may be used. The control parametersor settable parameters of the model are limited, such as associated withjoint rotation, so that the model may be transformed or manipulated todifferent body poses. Any human body modeling may be used. The modelingmay or may not also account for the shape of the person as well as pose.The pose deformation may be rigid, non-rigid, or a combination of both.A rotation matrix restricts polygons of the same body part to the samerotation. For rigid deformation, a regression function for each trianglemay be used to learn the pose deformation model to estimate based ontwists of the nearest joints. Given a deformation matrix, a regressionparameter is calculated. For non-rigid deformation, the distance betweenthe deformed template mesh and the training mesh is minimized in anoptimization constrained by smoothness and with a preference for similardeformation in adjacent polygons of the same body part. After training,the mesh model is fit to the scan or depth data by fitting usingdifferent values for the rigid rotation matrix. Other approaches may beused.

In other embodiments, a model, such as a pictorial structure model, islearned with machine training. The model includes body parts and/orlandmarks. The learnt model is fit to the scan data, such as fittingwith a joint likelihood maximization. Different body parts or landmarksin the model may be sequentially fit. Body part size or extent may beextrapolated from patient height. The region boundaries may beconstrained to be within learnt ranges based on height.

Other fitting may be used to determine the pose.

The template, landmarks, mesh, classifier output, and/or other resultsof the fitting provide values 31 for pose parameters. For example, thetemplate, mesh, or other model is labeled. A give relative positioningindicates the position of the body part, such as arms at the side of thetorso. The classifier or other output may be the label. The labelsprovide or are descriptors of the pose. A shape description vectorrepresenting the pose is determined. The descriptors indicate the valueof variable pose parameters, such as arm position, leg position, headorientation, resting side (e.g., torso orientation), or combinationsthereof. Alternatively, the pose is represented by the model withoutspecific labels (e.g., an image, point cloud, mesh, or renderingprovides the pose with and/or without values or positions for labeledbody parts).

In act 32, the patient on the bed of a medical scanner is sensed. For acurrent examination, the patient is positioned on the bed of the medicalscanner. Prior to positioning the bed within the scanner for scanning oronce the bed is positioned for scanning, the patient is sensed. For thecurrent examination, the pose is to conform to the previous or desiredpose determined in act 30. For example, the patient is sensed to acquiredata to determine the current pose for comparison with the desired pose(e.g., pose from a previous examination).

Any patient sensing may be used. For example, a depth camera or themedical scanner senses the patient. The depth camera or cameras are thesame or different than used for a previous examination. The camera orcameras may have the same or different perspectives as in a previousexamination. As another example, the medical scanner scans the patient(e.g., CT or MRI scan). The sensor (e.g., depth camera and/or scanner)captures data representing the patient on the bed of the medicalscanner. The data is a three-dimensional point cloud, cross-sectionimage, three-dimensional volume (e.g., voxels), or other collection ofdata representing the patient on the bed. The data is used “as is” fordetermining the pose or is further processed (e.g., filtered and/orcombined) to then be used to determine the pose.

In act 34, the pose of the patient is determined. The patient datacaptured in act 32 is used to determine the pose. The pose of thepatient as the patient lies on patient bed in anticipation of themedical scan for diagnosis is determined.

The determination uses the same or different approach as used fordetermining the desired pose of act 30. Since the protocol itself maynot represent the current pose of the patient, the captured data isused. Based on machine learnt classification, mesh fitting, modelfitting, template matching, or other approach, a processor determinesthe pose from the captured data.

The determined pose is parameterized in the same way as the desiredpose. For example, descriptors of body part positions are used. Asanother example, descriptors of body parts without position are used. Inyet another example, the pose is represented by an outline or image ofthe patient. The pose results 35 of the current patient pose are usedfor comparison with the results 31 for the desired pose.

In act 36, the desired pose is compared to the current pose. Forexample, the pose from a protocol or previous examination is compared tothe current pose. The processor compares to identify a match and/ordifferences.

In one embodiment, the comparison is of images, renderings, or fitmodels. By subtracting one from the other, differences in the pose areidentified. A distance threshold may be used, such that differencesgreater than a threshold amount are identified. Other image processingto find differences may be used.

In another embodiment, the comparison is of the descriptors. Theabsolute position may not be important, but deviations in arm positionsor head orientations may be detected and corrected before the scan. Bycomparing descriptors, matches and differences in the descriptors ofimportance to a given scan are found. All the descriptors or only asub-set may be compared. The descriptor for a given body part may have abinary (e.g., legs apart or together) or a restricted set of options(e.g., torso on side, on front, or on back). Where the options from thedesired pose and the current pose match, the comparison indicates thatthis aspect of the poses are the same. Where the options for a givenbody part from the desired pose and the current pose are different, thecomparison indicates that this aspect of the poses do not match or arenot aligned. The comparison is of measures or parameters of thepatients' pose.

In act 38, the processor transmits a change in pose based on thecomparison. The difference from the comparison indicates a change to bemade to the current pose. For example, the current pose is the personlaying on their left side. The desired pose is laying on their rightside. The difference in the descriptor for torso rotation is found bythe comparison. The change is in the torso rotation and/or is from leftside to right side. The pose for the body part from the desired poseindicate where the body part should be positioned. The pose from thecurrent pose indicates the wrong position. The change is indicated bythe correct position, the incorrect position, or a transition betweenthe two positions.

The change is transmitted so that the current pose will then match thedesired pose. All the changes to match, a sequence of changes, or anynumber of changes may be transmitted. The process may be iteratedthrough a hierarchy or sequence of successive changes (e.g., torsoorientation first, then leg, and them arm). The acts for currentposition determination and comparison are repeated. Once there are nodifferences, the current pose matches the desired pose. A generic idealpatient position or previous patient position is computed against thecurrent patient position to ensure a consistent and quality scan andreduce the involvement of the scanner operator.

The transmission is to a speaker and/or display. The change iscommunicated to the patient, physician, and/or technician. For example,transmission to the speaker is of audio instructions. The instructionsnote the body part and the position. For example, the determineddifference could result in a command “please place left arm down.” Otherverbal indications of the change may be used.

For visual indications, the change may be an instruction. For example,the “place left arm down” instruction is output to a display orprojected onto the patient, wall, or other surface. Other visualindications may be used. FIG. 5 shows an example. A projector projectsthe change onto the patient 14 and/or the patient bed. The legs are in acorrect position and the left arm is in an incorrect position as theleft arm should be placed above or beside the head. By projecting thecorrect pose onto the patient, differences may be seen. A rendering ofthe desired pose (e.g., rendering from scan data, point cloud, orgeneric model) is displayed as an image. An outline of the desired posemay be projected. The patient is then placed on the table in a way tomatch roughly the outline or image, or the patient is moved after beingon the table to match the outline or image.

The change may be highlighted, such as providing the body parts in thedesired pose in green (area 27) and providing body parts to be changedto the desired pose in red (area 28). The deviations in pose arereflected in the projection. Other highlighting may be used, such asoverlaying arrows or an animation of moving the body part to the desiredposition.

The display may be to a monitor or screen. For example, the desiredpose, an outline of the desired pose, descriptors of the desired pose orother visual representation is provided on a monitor of the medicalscanner or other workstation. The change may be reflected by comparisonon the display, such as showing the current pose or an image of thecurrent pose and the desire pose adjacent or overlaying each other. Thechange is reflected in the visual differences. The comparison on thescreen shows the change. Alternatively, the body parts shown,highlighting, or other emphasis based on the comparison increases thevisual focus on the body parts to be altered. The processor-basedcomparison is used to alter the display to show the desired change.

As represented in FIG. 2, this process may be repeated. After or oncethe patient pose is altered, the captured data reflects the alteration.The resulting current pose is compared with the desired pose. Wherethere are differences, then a recommendation to alter the current poseis output. Where there are not differences, then the diagnostic scan ortreatment scan may begin.

In act 40, the medical scanner scans the patient. After conforming thepose of the patient to the desired pose, the scan begins. The change inpose of the patient in response to the transmittal is confirmed by theprocessor. Alternatively, the change in pose is confirmed by thepatient, physician, or technician. Rather than repeat the capture of act32, determination of pose of act 34, and comparison of act 36, theoperator of the medical scanner confirms having performed the change orchanges, such as by activating the scan.

The patient bed moves the patient in the desired pose into a bore orother scan region. Alternatively, the patient bed remains in the bore orscan region. The scanning begins. Any type of diagnostic or treatmentscan may be used, such as x-ray, ultrasound, CT, MRI, PET, fluoroscopy,and/or combinations thereof. The examination is performed by the medicalscanner and with the patient in the desired pose.

The scan provides scan data representing the patient. The scan datarepresents a two-dimensional region or a three-dimensional region of thepatient. The scan data represents the patient at one period or includesrepresentations over time (e.g., frame of data or volume every fractionof a second).

In act 42, the processor spatially registers scan data from the currentexamination with the scan data from the previous examination. Anyspatial registration may be used, such as rigid or non-rigid. Thespatial registration allows for calculation of change over time. Forexample, a change in size of a spatially aligned tumor from differenttimes indicates whether treatment is satisfactory or whether treatmentis needed. The results of the current examination may be used for otherpurposes, such as diagnosis.

Since the pose is the same for both examinations, there is less likelyto be errors in the spatial alignment. The scan data from the differentexaminations more likely does not include differences without diagnosticsignificance. The registration may be more accurate when not dealingwith segmentation or other operations to account for differences inpose.

FIG. 4 shows one embodiment of a system 10 for patient positioning forscanning. The system implements the method of FIG. 1, FIG. 2, or adifferent method. By automatically detecting a current position andcomparing the current position to a desired position, the system 10assists in proper positioning of the patient for scanning. Rather thanrelying on the patient, physician, or technician to remember, review aprotocol, or review case notes, the position or change in position isindicated automatically for consistent positioning.

The system 10 is at a point of care for a patient 14, such as in a sameroom, hospital, or imaging center. In other embodiments, the processor20, memory 22, and/or display 24 are at other locations, such as adifferent building. The system 10 is used to position the patient forscanning. In one embodiment, the camera 18 is used to determine acurrent pose without an x-ray-based radiation scout scan of the patient14, limiting exposure of the patient to radiation.

The system 10 includes one or more cameras 18, the diagnostic imager 16,the processor 20, the memory 22, and the display 24. Additional,different, or fewer components may be provided. For example, the display24 is not provided, but a speaker is provided. As another example, auser input device is provided for the user to configure or activate thediagnostic imager 16. In yet another example, the camera 18 is notprovided, such as where scan data is used instead of a depth image.

The processor 20, memory 22, and display 24 are part of the diagnosticimager 16 in one embodiment, such as being a CT workstation. In otherembodiments, the processor 20, memory 22, and/or display 24 are part ofa separate computer, such as a separate workstation, personal computer,laptop, or tablet. The processor 20 and/or memory 22 may be part of aserver. In other embodiments, the memory 22 is a database separate fromthe processor 20.

The diagnostic imager 16 is a medical diagnostic imaging device orscanner. For example, the diagnostic imager 16 is a CT scanner with anx-ray source and detector connected on a gantry that moves relative to apatient bed. The patient bed includes robotics or motors for moving thepatient into or relative to a z axis through the bore and up and downwithin the bore. The diagnostic imager 16 scans the patient over a rangealong the longitudinal axis of the patient with part of the patientpositioned in an iso-center of the bore. In alternative embodiments, anMR, PET, SPECT, fluoroscopy, x-ray, ultrasound, or other medical imagingsystem is used instead of a CT scanner. In alternative embodiments, atreatment device or scanner, such as an x-ray scanner is used. Thediagnostic imager 16 may be used for diagnostic scanning and/ortreatment.

The camera 18 is a depth sensor. Stereo cameras, structured lighttransmission with a camera as the sensor, time-of-flight sensor with atransmitter, or other now known or later developed sensor fordetermining depth is provided as the camera 18. In one embodiment, thecamera 18 is an optical RGB-D camera.

The camera 18 is configured to detect a surface of a body or object. Thesurface is detected in three dimensions. The camera 18 captures an imageor images from which depth may be derived. Alternatively, the camera 18directly captures a 3D point cloud of different depth measurements.Image processing may be applied to remove background. Alternatively, thebackground remains and is dealt with as part of mesh fitting.

The patient 14 is positioned relative to the camera 18, such as on thebed of the diagnostic imager 16 while the bed is outside of the bore ofthe diagnostic imager 16. The camera 18 may be positioned to image thepatient 14 while the patient 14 is within the bore. Where multiplecameras 18 are provided, the cameras 18 are directed to view the patient14 from different directions. Depth data representing the surface of thepatient is acquired from the different cameras 18 and used together tocreate a unified point cloud or surface representation.

The surface of the patient 14 is the skin of the patient. Alternatively,the surface of the patient 14 is clothing of the patient. The surfacemay be low pass filtered to remove high frequency variation. Depthinformation for combinations of skin and clothing may be detected.

The processor 20 is a general processor, central processing unit,controller, control processor, graphics processor, digital signalprocessor, three-dimensional rendering processor, image processor,application specific integrated circuit, field programmable gate array,digital circuit, analog circuit, combinations thereof, or other nowknown or later developed device for accessing data, determining pose,comparing poses, transmitting changes in pose, controlling scanning,and/or spatially registering scan data from different times. Theprocessor 20 is a single device or multiple devices operating in serial,parallel, or separately. The processor 20 may be a main processor of acomputer, such as a laptop or desktop computer, or may be a processorfor handling some tasks in a larger system, such as in a medical imagingsystem. The processor 20 is configured by instructions, design,hardware, and/or software to be able to perform the acts discussedherein.

The processor 20 is configured to determine a pose of the body from asurface captured by the camera 18 or from scan data captured by thediagnostic imager 16. The processor 20 is configured to identify adifference in the pose of the body from another pose. The other pose isa desired pose, such as from a protocol or a pose derived from data froma previous scan. The processor 20 may look up the other pose or maydetermine the other pose from scan data or a depth camera image acquiredat a previous time. Based on the comparison, the processor 20 isconfigured to identify a change in pose of the current patient to matchthe desired pose. The change may be a difference in pose. The processor20 is configured to transmit the change or pose information to correctthe current pose, such as transmitting an image with a graphic,highlighting, or animation.

The memory 22 is a graphics processing memory, a video random accessmemory, a random access memory, system memory, random access memory,cache memory, hard drive, optical media, magnetic media, flash drive,buffer, database, combinations thereof, or other now known or laterdeveloped memory device for storing data or video information. Thememory 22 is part of the diagnostic imager 16, part of a computerassociated with the processor 20, part of a database, part of anothersystem, a picture archival memory, or a standalone device.

The memory 22 stores data used by the processor 20. For example, thememory 22 stores a protocol or a desired pose, captured data, and/orscan data. In another example, the memory 22 stores a model, templates,machine-learnt classifiers, and/or other data used to determine andcompare poses. As another example, the memory 22 stores data used inprocessing, such as a mesh, fitted mesh, parameters used in fitting,and/or matrices. In yet another example, the memory 22 stores results,such as pose vectors, differences in pose, images, graphic overlays,highlighting, or changes. Any data used, input to, output by, or createdfor the acts discussed herein may be stored in the memory 22 or anothermemory.

The memory 22 or other memory is alternatively or additionally acomputer readable storage medium storing data representing instructionsexecutable by the programmed processor 20 and/or diagnostic imager 16.The instructions for implementing the processes, methods and/ortechniques discussed herein are provided on non-transitorycomputer-readable storage media or memories, such as a cache, buffer,RAM, removable media, hard drive or other computer readable storagemedia. Non-transitory computer readable storage media include varioustypes of volatile and nonvolatile storage media. The functions, acts ortasks illustrated in the figures or described herein are executed inresponse to one or more sets of instructions stored in or on computerreadable storage media. The functions, acts or tasks are independent ofthe particular type of instructions set, storage media, processor orprocessing strategy and may be performed by software, hardware,integrated circuits, firmware, micro code and the like, operating alone,or in combination. Likewise, processing strategies may includemultiprocessing, multitasking, parallel processing, and the like.

In one embodiment, the instructions are stored on a removable mediadevice for reading by local or remote systems. In other embodiments, theinstructions are stored in a remote location for transfer through acomputer network or over telephone lines. In yet other embodiments, theinstructions are stored within a given computer, CPU, GPU, or system.

The display 24 is a liquid crystal display (LCD), an organic lightemitting diode (OLED), a flat panel display, a solid state display, acathode ray tube (CRT), a projector, a printer, or other now known orlater developed display device for outputting an image withhighlighting, graphics showing change, graphics showing a pose,animation showing change, instructions, or other information. Thedisplay 24 may be part of a user interface.

The display 24 is configured by a display plane buffer or data providedby the processor 20. The display 24 is configured to indicate resultsfrom comparing poses, a desired pose, differences in poses, a change toprovide the desired pose, or other information.

In one embodiment, the display 24 is a projector configured to indicatea change to reduce a difference between a desired pose and the currentpose of a patient. The desired pose is projected onto the body of thepatient and/or patient bed with the difference from the current posehighlighted.

Using the camera captured data, the processor 20 may determine alocation of the eyes of the patient. The projection may include a dark(e.g., black) region projected to the eyes of the patient.

FIG. 5 shows another embodiment of the system 10. The system 10 ensuresconsistent patient positioning during subsequent image acquisitions forimproved comparison and registration. The previous volume or RGB-D datais used to model the patient position. The RGB-D image from the camera18 and/or possibly diagnostic scan from the scanner 16 is used to assesscurrent patient position. The previous scan and/or RGB-D data (ifavailable) is used to compute the desired patient orientation andposition. The required changes to arrive at the ideal or previouspatient position is then communicated via a monitor or more intuitivelyby an attached projector 24. In the diagram, the projector 24 avoids(projects black) the region 29 of the patient's eyes. Green body regions27 are projected onto properly aligned body parts. Red outlines 28 areprojected on improperly aligned parts or where a part should bepositioned, such as projecting an outline as to where the improperlyaligned part should be orientated. In the case of a monitor, an overlayof the expected position on the RGB camera view of the patient may beperformed. Similar region highlighting colors or graphics may beemployed on the monitor.

While the invention has been described above by reference to variousembodiments, it should be understood that many changes and modificationscan be made without departing from the scope of the invention. It istherefore intended that the foregoing detailed description be regardedas illustrative rather than limiting, and that it be understood that itis the following claims, including all equivalents, that are intended todefine the spirit and scope of this invention.

1. A method for patient positioning for scanning, the method comprising:determining a first pose of a patient from a first examination, thefirst pose determined from a depth camera image, scan data from thefirst examination, or both; sensing a patient on a bed of a medicalscanner for a second examination at a different time than the firstexamination, the sensing being by a depth camera, the medical scanner,or both; determining a second pose of the patient from the sensing;comparing the first pose to the second pose; and transmitting a changein pose so that the second pose matches the first pose, the change inpose based on the comparing.
 2. The method of claim 1 whereindetermining the first and second poses comprises fitting a parameterizeddeformable model to a point cloud of the depth camera image, to scandata, or to both.
 3. The method of claim 1 wherein determining the firstand second poses comprises identifying relative position of landmarks.4. The method of claim 1 wherein determining the first and second posescomprises determining arm position, leg position, head orientation,resting side, or combinations thereof.
 5. The method of claim 1 whereindetermining the first pose comprises determining the first pose from thefirst examination comprising a previous examination for diagnosis priorto diagnosis where the second examination occurs after treatment basedon the diagnosis.
 6. The method of claim 1 wherein determining the firstpose comprises determining the first pose from the first examinationwhere the first pose of the patient was established without a plan fortreatment.
 7. The method of claim 1 wherein sensing comprises sensingwith the depth camera, the sensing providing a three-dimensional pointcloud, and wherein determining the second pose comprises determiningfrom the three-dimensional point cloud.
 8. The method of claim 1 whereinsensing comprises scanning the patient by the medical scanner, thesensing providing scan data representing the patient, and whereindetermining the second pose comprises determining from the scan data. 9.The method of claim 1 wherein the first and second poses areparameterized by descriptors of arm position, head orientation, legposition, torso orientation, or combinations thereof and whereincomparing comprises comparing the descriptors.
 10. The method of claim 1wherein comparing comprises identifying a difference of the second posefrom the first pose.
 11. The method of claim 1 wherein transmittingcomprises outputting audio of the change.
 12. The method of claim 1wherein transmitting comprises displaying the change.
 13. The method ofclaim 12 wherein displaying comprises projecting a body part in aposition reflecting the change.
 14. The method of claim 1 furthercomprising performing the second examination with the medical scannerand spatially registering the scan data of the first examination withscan data of the second examination.
 15. A method for patientpositioning for scanning, the method comprising: capturing datarepresenting a patient on a bed of a medical scanner, the capturingbeing by a depth camera, the medical scanner, or both; determining afirst pose of the patient from the data; comparing the first pose to asecond pose; transmitting a change in pose of the patient on the bed sothat the first pose matches the second pose, the change in pose based onthe comparing; and scanning, with the medical scanner, the patient afterconforming to the change in the pose.
 16. The method of claim 15 whereincapturing comprises capturing by the depth camera.
 17. The method ofclaim 15 wherein comparing comprises comparing the first pose to thesecond pose, the second pose comprising a pose from a protocol.
 18. Themethod of claim 15 wherein comparing comprises comparing the first poseto the second pose, the second pose comprising a pose from scan data,depth image, or both of a previous examination of the patient.
 19. Asystem for patient positioning for scanning, the system comprising: adiagnostic imager having a patient bed; a camera configured to detect asurface of a body on the patient bed; a processor configured todetermine a pose of the body from the surface and identify a differencein the pose of the body from another pose; and a display configured toindicate a change to reduce the difference.
 20. The system of claim 19wherein the display comprises a projector configured to project theother pose onto the body on the patient bed with the differencehighlighted while avoid projection at eyes of the body.